SOTAVerified

Malware Detection

Malware Detection is a significant part of endpoint security including workstations, servers, cloud instances, and mobile devices. Malware Detection is used to detect and identify malicious activities caused by malware. With the increase in the variety of malware activities on CMS based websites such as malicious malware redirects on WordPress site (Aka, WordPress Malware Redirect Hack) where the site redirects to spam, being the most widespread, the need for automatic detection and classifier amplifies as well. The signature-based Malware Detection system is commonly used for existing malware that has a signature but it is not suitable for unknown malware or zero-day malware

Source: The Threat of Adversarial Attacks on Machine Learning in Network Security - A Survey

Papers

Showing 6170 of 431 papers

TitleStatusHype
Detecting DGA domains with recurrent neural networks and side informationCode0
Level Up with ML Vulnerability Identification: Leveraging Domain Constraints in Feature Space for Robust Android Malware DetectionCode0
DeepXplore: Automated Whitebox Testing of Deep Learning SystemsCode0
DetectBERT: Towards Full App-Level Representation Learning to Detect Android MalwareCode0
Evaluating Explanation Methods for Deep Learning in SecurityCode0
Classification with Costly Features in Hierarchical Deep SetsCode0
DeepSign: Deep Learning for Automatic Malware Signature Generation and ClassificationCode0
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep LearningCode0
Accelerating Malware Classification: A Vision Transformer SolutionCode0
Deep learning at the shallow end: Malware classification for non-domain expertsCode0
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